Optimization of Image Mosaic Algorithm Based on Parallel I/O and Dynamic Grouping

Image mosaic of a great number of remote sensing images with large scale is commonly complicated and time-consuming.Parallel computing is recently considered as an effective way to solve the problem of enormous computation caused by its complicated algorithm and massive data amount.But traditional parallelization of mosaic algorithm is time-consuming in I/O performance.Furthermore,the registration and blending in mosaic is time-consuming too,but there is no effective parallel strategy of data splitting to solve this problem.For that,an optimized image mosaic algorithm with Parallel I/O and dynamic grouped parallel strategy based on minimal spanning tree is proposed in this paper.Through experimental and comparative analysis,its outstanding parallel efficiency and perfect linear speedup is showed in this paper.